Industrial Engineering Journal ›› 2012, Vol. 15 ›› Issue (1): 23-27.

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A Bee Evolutionary Particle Swarm Optimization Algorithm for Vehicle Routing Problem

  

  1. College of Management,University of Shanghai for Science and Technology, Shanghai 200093,China
  • Online:2012-02-29 Published:2012-03-13
  • Supported by:

    上海市研究生创新基金资助项目(JWCXSL1022);教育部人文社会科学规划基金资助项目(10YJA630187);高等学校博士点基金资助项目(20093120110008);上海市重点学科建设资助项目(S30504)

Abstract: The vehicle routing problem (VRP) is discussed in this paper. There are studies that solve VRP by using particle swarm optimization (PSO) algorithm. However, with traditional PSO, it has slow convergence rate and a local optimum may be obtained. In order to improve the performance of PSO, an algorithm called bee evolutionary particle swarm optimization(BEPSO) is presented for VRP in this paper. By this algorithm, the best particle regarded as the queen crosses with the selected drones randomly. In this way, it takes the advantage of the best individuals information. At the same time, some drones are randomly generated and crossed with the queen such that diversity is enlarged. Experimental test shows that the proposed algorithm has better global search ability than the existing ones.

Key words: bee evolutionary, vehicle routing problem (VRP), particle swarm optimization (PSO)